Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
NA NA 4 NA NA NA 5 NA NA NA 16 NA 12 9 NA NA 5 5 NA NA 2 NA NA 7 NA NA NA 13 NA NA 11 NA NA 0 NA 5 NA NA 14 NA 1 NA 11 NA 12 NA NA NA 6 NA NA NA NA NA NA NA NA NA NA 7 NA NA NA 8 NA NA NA NA 11 NA 9 5 NA NA -3 NA 7 NA 13 NA NA 2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 7 NA NA NA NA NA 10 NA NA 8 8 2 NA NA NA NA NA 6 3 NA NA 3 9 NA -1 NA NA 12 NA NA NA NA 4 7 NA 7 2 13 14 11 14 NA 8 12 2 15 14 NA NA 4 NA NA NA NA 4 NA 8 7 NA NA 6 NA NA 7 NA 9 17 NA NA 16 NA 7 NA 12 9 NA 9 0 3 NA 5 4 14 NA 15 13 9 11 NA 5 1 17 NA 6 9 7 NA 6 11 0 NA 16 7 NA 15 10 7 13 3 0 11 NA 6 -4 NA 4 16 13 NA 0 NA 6 4 4 2 13 NA 15 6 4 13 13 6 11 9 12 2 6 6 -1 4 11 2 7
Data Y:
9 17 NA 11 12 15 NA 11 10 6 NA 10 NA NA 13 12 NA NA 15 6 NA 6 17 NA 13 14 9 NA 12 2 NA 7 5 NA 11 NA 6 4 NA 10 NA 6 NA 17 NA 4 4 6 NA 10 13 15 3 9 19 7 4 5 9 NA 12 5 12 NA 12 11 9 9 NA 9 NA NA 7 7 NA 4 NA 13 NA 10 5 NA 13 6 14 13 11 6 12 9 17 7 13 12 6 11 9 NA 11 15 6 12 3 NA 9 10 NA NA NA 12 12 10 12 12 NA NA 4 12 NA NA 13 NA 14 6 NA 9 10 6 17 NA NA 12 NA NA NA NA NA NA 14 NA NA NA NA NA 13 15 NA 9 12 18 11 NA 4 NA NA 12 9 NA 11 16 NA 6 NA NA 15 9 NA 5 NA 13 NA NA 10 NA NA NA 15 NA NA NA 9 NA NA NA NA 13 NA NA NA 9 NA NA NA 9 NA NA NA 15 NA NA 7 NA NA NA NA NA NA NA 11 NA NA 10 NA NA NA 7 NA 13 NA NA NA NA NA 15 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
library(psychometric) x <- x[!is.na(y)] y <- y[!is.na(y)] y <- y[!is.na(x)] x <- x[!is.na(x)] bitmap(file='test1.png') histx <- hist(x, plot=FALSE) histy <- hist(y, plot=FALSE) maxcounts <- max(c(histx$counts, histx$counts)) xrange <- c(min(x),max(x)) yrange <- c(min(y),max(y)) nf <- layout(matrix(c(2,0,1,3),2,2,byrow=TRUE), c(3,1), c(1,3), TRUE) par(mar=c(4,4,1,1)) plot(x, y, xlim=xrange, ylim=yrange, xlab=xlab, ylab=ylab, sub=main) par(mar=c(0,4,1,1)) barplot(histx$counts, axes=FALSE, ylim=c(0, maxcounts), space=0) par(mar=c(4,0,1,1)) barplot(histy$counts, axes=FALSE, xlim=c(0, maxcounts), space=0, horiz=TRUE) dev.off() lx = length(x) makebiased = (lx-1)/lx varx = var(x)*makebiased vary = var(y)*makebiased corxy <- cor.test(x,y,method='pearson', na.rm = T) cxy <- as.matrix(corxy$estimate)[1,1] load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistic',1,TRUE) a<-table.element(a,'Variable X',1,TRUE) a<-table.element(a,'Variable Y',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm','Mean',''),header=TRUE) a<-table.element(a,mean(x)) a<-table.element(a,mean(y)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased.htm','Biased Variance',''),header=TRUE) a<-table.element(a,varx) a<-table.element(a,vary) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased1.htm','Biased Standard Deviation',''),header=TRUE) a<-table.element(a,sqrt(varx)) a<-table.element(a,sqrt(vary)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/covariance.htm','Covariance',''),header=TRUE) a<-table.element(a,cov(x,y),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/pearson_correlation.htm','Correlation',''),header=TRUE) a<-table.element(a,cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/coeff_of_determination.htm','Determination',''),header=TRUE) a<-table.element(a,cxy*cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ttest_statistic.htm','T-Test',''),header=TRUE) a<-table.element(a,as.matrix(corxy$statistic)[1,1],2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value (2 sided)',header=TRUE) a<-table.element(a,(p2 <- as.matrix(corxy$p.value)[1,1]),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value (1 sided)',header=TRUE) a<-table.element(a,p2/2,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'95% CI of Correlation',header=TRUE) a<-table.element(a,paste('[',CIr(r=cxy, n = lx, level = .95)[1],', ', CIr(r=cxy, n = lx, level = .95)[2],']',sep=''),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Degrees of Freedom',header=TRUE) a<-table.element(a,lx-2,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of Observations',header=TRUE) a<-table.element(a,lx,2) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') library(moments) library(nortest) jarque.x <- jarque.test(x) jarque.y <- jarque.test(y) if(lx>7) { ad.x <- ad.test(x) ad.y <- ad.test(y) } a<-table.start() a<-table.row.start(a) a<-table.element(a,'Normality Tests',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('jarque.x'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('jarque.y'),'</pre>',sep='')) a<-table.row.end(a) if(lx>7) { a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('ad.x'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('ad.y'),'</pre>',sep='')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') library(car) bitmap(file='test2.png') qq.plot(x,main='QQplot of variable x') dev.off() bitmap(file='test3.png') qq.plot(y,main='QQplot of variable y') dev.off()
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation